Computational Analysis of Retinal Regulatory Interactions: structure and dynamics

描述（申请人提供）：了解视网膜调控网络有助于阐明视网膜发育和视网膜疾病的分子基础。尽管对视网膜调节因子和元件的了解有所增加，并且已经确定了几种与视网膜疾病相关的转录因子（TF）突变，但对视网膜调节网络的总体理解仍然相当有限。我们的长期目标是了解视网膜调节网络的结构和动态。为此，我们在此提出了一种计算方法，通过整合当前的知识和来自高通量实验的各种数据集，来预测与视网膜调节相关的蛋白质- dna和蛋白质-蛋白质相互作用。我们还提出用实验来验证这一预测。我们不仅对静态相互作用的预测感兴趣，而且对相互作用的条件依赖性转录活性也感兴趣。为了实现我们的目标，我们有四个具体目标：(1)识别视网膜相关的顺式调控元件及其调控靶点；(2)确定视网膜相关基因的相互作用转录因子；(3)表征视网膜调控网络的动力学；(4)生物信息学预测的实验验证。除了研究视网膜疾病之外，本提案中开发的计算程序也应该对广泛的社区普遍有用。

DESCRIPTION (provided by applicant): An understanding of retinal regulatory networks can help elucidate the molecular basis of retinal development and retinal diseases. Although gains in knowledge about retinal regulatory factors and elements have been made and several transcription factor (TF) mutations associated with retinal disease have been identified, overall understanding of retinal regulatory networks is still rather limited. Our long-term goal is to attain understanding of the structure and dynamics of retinal regulatory networks. To that end, we here propose a computational approach to predict protein-DNA and protein-protein interactions related to the retinal regulation by integrating current knowledge and a variety of data sets from high-throughput experiments. We also propose to verify the prediction experimentally. We are interested not only in the prediction of static interactions, but also in the condition-dependent transcriptional activity of interactions. To achieve our objective, we have four Specific Aims: (1) identification of retina-related cis-regulatory elements and their regulatory targets, (2) determination of interacting transcription factors that co-regulate retina-related genes, (3) characterization of the dynamics of the retinal regulatory networks, and (4) experimental verification of bioinformatics predictions. Beyond investigation of retinal disease, the computational programs developed in this proposal should also be generally useful for a broad community.